Bayesian Uncertainty Quantification for CUORE & CUPID

The search for neutrinoless double-beta decay is one of the foremost avenues to determine the nature of neutrino mass, understand the matter/anti-matter asymmetry of the Universe, and uncover signs of physics beyond the Standard Model. One of the leading detector technologies enabling the pursuit of this hypothesized nuclear decay are cryogenic calorimeters, as exemplified by the CUORE experiment, along with its planned successor, CUPID. These experiments instrument hundreds to thousands of single-crystal detector channels, requiring a significant number of nuisance parameters to describe detector performance with high fidelity and specificity. This talk discusses efforts and progress to expand Bayesian analysis infrastructure and uncertainty quantification within CUORE and CUPID, including use of high-performing gradient-aware samplers, and investigating the impact of such channel-dependent nuisance parameters on discovery sensitivity. This work has applications towards searches for neutrinoless double-beta decay, along with other analyses of interest to the experiments.